H
Hsien-Hsin Chou
Researcher at National Ilan University
Publications - 7
Citations - 158
Hsien-Hsin Chou is an academic researcher from National Ilan University. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 4, co-authored 6 publications receiving 134 citations.
Papers
More filters
Journal ArticleDOI
Turbulent-PSO-Based Fuzzy Image Filter With No-Reference Measures for High-Density Impulse Noise
TL;DR: The experimental results confirm that the TPFF attains an excellent quality of restored images in terms of peak signal-to-noise ratio, mean square error, and mean absolute error even when the noise rate is above 0.5 and without the aid of noise-free images.
Journal ArticleDOI
Variable-dimensional vector modulation for perceptual-based DWT blind audio watermarking with adjustable payload capacity
TL;DR: The effectiveness of the proposed VDVM scheme is proven using the perceptual evaluation of audio quality and bit error rates of recovered watermarks under various signal processing attacks and the imperfection of applying quantization index modulation in the open-loop case is rectified.
Journal ArticleDOI
Perceptual-based DWPT-DCT framework for selective blind audio watermarking
TL;DR: Experimental results show that the proposed DWPT-DCT scheme is comparable to three recently developed methods in robustness while it is the only scheme surviving the amplitude scaling attack.
Journal ArticleDOI
Incorporation of perceptually adaptive QIM with singular value decomposition for blind audio watermarking
TL;DR: Experimental results confirm that the combination of the DWPT, SVD, and adaptive QIM achieves imperceptible data hiding with satisfying robustness and payload capacity.
Journal ArticleDOI
A high-capacity QRD-based blind color image watermarking algorithm incorporated with AI technologies
TL;DR: In this paper , a high capacity QR decomposition (QRD) based blind watermarking algorithm with artificial intelligence (AI) technologies for color images was proposed, which involves dividing the host image into non-overlapping blocks of size 4 × 4 pixels and then applying the QRD to each block.